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Titlebook: Advances in Artificial Intelligence; 19th Conference of t Enrique Alba,Gabriel Luque,Rodrigo Gil-Merino Conference proceedings 2021 Springe

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期刊全稱(chēng)Advances in Artificial Intelligence
期刊簡(jiǎn)稱(chēng)19th Conference of t
影響因子2023Enrique Alba,Gabriel Luque,Rodrigo Gil-Merino
視頻videohttp://file.papertrans.cn/147/146720/146720.mp4
學(xué)科分類(lèi)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Advances in Artificial Intelligence; 19th Conference of t Enrique Alba,Gabriel Luque,Rodrigo Gil-Merino Conference proceedings 2021 Springe
影響因子This book constitutes the refereed proceedings of the 19th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2020, which was cancelled due to the COVID-19 pandemic, amalgamated with CAEPIA 2021, and held in Malaga, Spain, during September 2021..The 25 full papers presented were carefully selected from 40 submissions. The Conference of the Spanish Association of Artificial Intelligence (CAEPIA) is a biennial forum open to researchers from all over the world to present and discuss their latest scientific and technological advances in Antificial Intelligence (AI). The book is subdivided into the following topical headings: machine learning, optimization and search, and real-world applications. It covers such themes as ambient intelligence and smart environments; computer vision and robotics; constraints, search and planning; creativity and A.I.; education and A.I.; explainable and responsible A.I.; foundation, models and applications of A.I, andothers..
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Studying the Effect of Different , Norms in the Context of Time Series Ordinal Classificationook to the public. In principle it is about thermodynamics, especially the simulation of thermo?uid systems. In popular opinion, thermodynamics is considered to be highly abstract and di?cult to comprehend with its many symbols. We endeavor to show the reader how simple and beautiful thermodynamics
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Towards Fairness in Classification: Comparison of Methods to Decrease Biaso certain free parameters (e.g., chord line (Leifsson and Koziel 2015a, b, c), time, or frequency (Koziel et al. 2006a, b)), are challenging to simulation-driven design optimization. The surrogate-based optimization techniques described in the previous chapters directly handled the relevant response
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Hypothesis Scoring and Model Refinement Strategies for FM-Based RANSACf development and delivery of quality simulations.Offers evi.This book focuses on evidence-based standards for simulation in nursing education. The foundational principle of simulation excellence and its relevance to nursing is defined and infuses throughout the book. ?It also discusses necessary co
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